Abstract

This study presents a Smart Enterprise Risk Governance System that integrates predictive analytics to enhance cyber threat prioritization and strategic decision making across complex organizational environments. The system is designed to address persistent limitations in traditional risk governance frameworks, which often rely on static assessments, reactive controls, and fragmented oversight structures that are insufficient for evolving cyber threat landscapes. By embedding advanced analytics, machine learning models, and enterprise risk governance principles, the proposed system enables continuous risk sensing, dynamic prioritization, and alignment of cyber risk responses with organizational objectives. The framework combines internal security telemetry, third party risk indicators, compliance data, and external threat intelligence into a unified analytical layer. Predictive models are applied to forecast threat likelihood, potential impact, and propagation pathways, allowing organizations to rank cyber risks based on real time exposure and business criticality. Governance workflows are integrated to ensure that prioritized risks trigger proportionate controls, executive oversight, and accountability mechanisms across operational, tactical, and strategic levels. A core contribution of this study is the linkage between predictive cyber analytics and enterprise governance structures, ensuring that insights generated by algorithms translate into actionable policy, investment, and resilience decisions. The system supports board level visibility through risk dashboards, scenario simulations, and early warning indicators that strengthen risk informed governance. It also enables adaptive policy updates, resource optimization, and continuous assurance in line with regulatory and industry expectations. The proposed Smart Enterprise Risk Governance System advances cyber risk management from a defensive technical function to a value driven governance capability. By integrating predictive analytics with structured governance processes, the system enhances organizational agility, reduces decision latency, and improves preparedness against high impact cyber threats. This approach provides a scalable and transferable model for enterprises seeking to strengthen cyber resilience, regulatory alignment, and strategic risk oversight in increasingly digitized and interconnected environments. Overall, the study contributes to enterprise cybersecurity scholarship by offering a governance centric architecture that integrates foresight, accountability, and analytics to support proactive risk cultures, cross functional coordination, measurable outcomes, and sustained trust across digital ecosystems globally today under diverse regulatory conditions, sectors, and maturity levels worldwide contexts.